1. Field of the Invention
The present disclosure relates to a system and method for providing health analysis. Specifically, the present disclosure relates to a symptom analysis application and method for creating, analyzing, individualizing, geo-locating, and displaying information regarding symptoms of allergy, asthma, sinus headaches, migraine, arthritis, and other medical conditions induced by a person's unique responses to environmental exposures to allergens, air pollutants, and weather elements instantaneously in real time.
2. Description of Related Art
A large proportion of the population suffers from allergy symptoms. Allergic reactions are typically caused by the interaction of a person's immune system with external and environmental factors. For example, foreign proteins such as those found in pollens, molds, and dust mites may cause an immune reaction in any person having a particular genetic sensitivity. If the immune reaction induced by these foreign proteins involves certain antibodies, the possibility of an allergic reaction exists.
However, each patient with allergy or asthma issues is unique and will respond differently to different aggravating factors. For example, one person may be very sensitive to air pollutants but have little reaction to mold spores, whereas another person may have no reaction to air pollutants but a severe reaction to pollens.
Allergic reactions may range from mild annoyances to severe and potentially life-threatening events. For example, asthma is caused by allergic reactions within the airways of the lungs. If left untreated and uncontrolled, asthma may be life threatening or result in a form of permanent emphysema. In order to prevent such long-term effects, it is desirable to predict when and where allergy and/or asthma events may occur.
However, an accurate prediction requires accurate information as to a person's activities and health. Simply asking the person about their activities and health introduces a high degree of subjectivity into the prediction, and therefore reduces the accuracy of the prediction. Moreover, asking the person to provide information regarding past events may introduce hindsight bias or other memory errors, and thus further reduce the accuracy of the prediction.
To that end, there exists a need for a system and method to obtain both subjective and objective information, in real-time, regarding a person's health. Moreover, there exists a need for a system and method to correlate this information with environmental data for the person's particular location, also in real-time. The proliferation of mobile devices (such as smartphones) provides a possible path to such a solution, but is fraught with difficulties. For example, inefficiencies arising out of existing tools may result in increased bandwidth and/or computational footprint. Moreover, existing tools may be unduly invasive, leading potential users to reject them. These challenges, particular to the Internet and the field of mobile-device-assisted health monitoring, make it difficult to provide an effective solution. To overcome such a problem specifically arising in the realm of computer networks, a solution necessarily rooted in computer technology must be developed.